Apollo Autonomous Driving USA LLC (20240210939). CAMERA IMAGE COMPRESSION FOR AUTONOMOUS DRIVING VEHICLES simplified abstract
Contents
- 1 CAMERA IMAGE COMPRESSION FOR AUTONOMOUS DRIVING VEHICLES
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 CAMERA IMAGE COMPRESSION FOR AUTONOMOUS DRIVING VEHICLES - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about Camera Image Data Processing in Autonomous Vehicles
- 1.13 Original Abstract Submitted
CAMERA IMAGE COMPRESSION FOR AUTONOMOUS DRIVING VEHICLES
Organization Name
Apollo Autonomous Driving USA LLC
Inventor(s)
Guoli Shu of Sunnyvale CA (US)
Manjiang Zhang of Sunnyvale CA (US)
CAMERA IMAGE COMPRESSION FOR AUTONOMOUS DRIVING VEHICLES - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240210939 titled 'CAMERA IMAGE COMPRESSION FOR AUTONOMOUS DRIVING VEHICLES
Simplified Explanation
The patent application describes a method for processing camera image data in an autonomous driving vehicle using a main compute unit, an FPGA unit, and a GPU. The method involves receiving full raw image data and partial compressed image data, transmitting the partial compressed image data to a remote driving operation center, and using the full raw image data for environment perception.
- The method balances cost and latency in processing camera image data in an autonomous driving vehicle.
- It involves receiving full raw image data and partial compressed image data from different sources.
- The partial compressed image data is transmitted to a remote driving operation center.
- The full raw image data is used for environment perception and is also compressed by the GPU for offline processing.
Key Features and Innovation
- Cost-latency balanced method for processing camera image data in an autonomous driving vehicle.
- Utilizes a main compute unit, FPGA unit, and GPU for efficient data processing.
- Receives full raw image data and partial compressed image data for different purposes.
- Transmits partial compressed image data to a remote driving operation center.
- Compresses full raw image data for offline processing using the GPU.
Potential Applications
- Autonomous driving vehicles
- Remote driving operation centers
- Image data processing systems
Problems Solved
- Balancing cost and latency in processing camera image data
- Efficient utilization of raw and compressed image data
- Enhancing environment perception in autonomous driving vehicles
Benefits
- Improved efficiency in processing camera image data
- Enhanced environment perception for safer driving
- Cost-effective data processing methods
Commercial Applications
Autonomous driving technology: Enhancing image data processing efficiency in autonomous vehicles can lead to safer and more reliable self-driving systems, attracting potential commercial applications in the automotive industry.
Prior Art
Readers can explore prior patents related to image data processing in autonomous vehicles, FPGA technology, and GPU utilization in data compression to gain a deeper understanding of the innovation presented in this patent application.
Frequently Updated Research
Researchers may find updated studies on cost-effective methods for processing camera image data in autonomous vehicles, advancements in FPGA technology for data processing, and GPU optimization for image compression.
Questions about Camera Image Data Processing in Autonomous Vehicles
How does the method balance cost and latency in processing camera image data?
The method balances cost and latency by receiving full raw image data for environment perception and transmitting partial compressed image data for remote driving operation centers, optimizing data processing efficiency.
What are the potential applications of this technology beyond autonomous driving vehicles?
The technology can be applied in remote driving operation centers, image data processing systems, and other industries requiring efficient data processing methods.
Original Abstract Submitted
a cost-latency balanced method of processing camera image data in an autonomous driving vehicle (adv) is described. the adv includes a main compute unit coupled to an fpga unit and a graphical processing unit (gpu). the method includes receiving, by the main compute unit, a full raw image data and a partial compressed image data from the fpga unit, the full raw image being raw image data captured by all cameras mounted on the adv, and the partial compressed image data being compressed from a partial raw image data captured by a subset of the cameras mounted on the adv. the method further includes transmitting the partial compressed image data to a remote driving operation center; and consuming the full raw image data for environment perception, and the full raw image data is also compressed into a full compressed image data by the gpu for use in offline processing.
